Jira copilot: A practical guide to AI integration in 2025

Let’s be honest, the promise of integrating AI with Jira sounds incredible. We all have this vision of an intelligent assistant that finally tames our sprawling backlog, answers questions instantly, and frees us up from the endless cycle of status updates and manual ticket grooming. The goal is simple: get more done with less hassle and make project information easy to find for everyone, not just the people who speak fluent Jira Query Language (JQL).

But if you’ve actually tried to set up a "Jira Copilot," you might have found the reality to be… well, a bit of a letdown. A quick scroll through Reddit or community forums shows a common theme of frustration. People hit a wall with AI assistants that give wrong answers, forget what was said two seconds ago, and require a Ph.D. in systems administration just to get running.

People hit a wall with AI assistants that give wrong answers, forget what was said two seconds ago, and require a Ph.D. in systems administration just to get running.

Reddit

The hype around AI is massive, but the execution often feels half-baked. This guide is here to give you a clear-eyed look at the options for a Jira Copilot, the real-world problems you’ll likely run into, and a much better way to bring AI into your workflow that actually works.

What is a Jira Copilot?

First things first, let’s clear up a common point of confusion. "Jira Copilot" isn’t a specific, official product you can download from a single store. It’s more of a catch-all term for using an AI assistant to chat with your Jira data. Think of it like having a conversation with your project board instead of clicking through endless menus.

When people talk about setting up a Jira Copilot, they’re usually trying one of three main routes:

1. Microsoft Copilot integrations: This involves using Microsoft’s AI, typically through an app like Microsoft Teams, to ask questions about what’s happening in your Jira projects.

2. Atlassian’s native AI: This means using the built-in Atlassian Intelligence (which you might have heard of under its old name, Rovo) that’s baked directly into Jira and other Atlassian tools.

3. Third-party AI platforms: These are specialized tools built from the ground up to connect deeply with Jira and all your other company documents to provide some seriously advanced and customizable automation.

Each path has its own bumps and benefits, and figuring out which one is right for you means understanding what they can (and can’t) do.

The official Jira Copilot integrations: Microsoft Copilot vs. Atlassian Intelligence

Let’s start with the big names. Both Microsoft and Atlassian have their own "official" ways to give you a copilot-like experience for Jira. On paper, they sound great. In practice, they come with some significant strings attached.

Microsoft’s Jira Copilot connector

Microsoft has an official Atlassian Jira Cloud connector for Microsoft 365 Copilot. The big idea is to let you query Jira without ever leaving the comfort of Microsoft Teams or another M35 app. It’s built for the person who lives in chat all day and just wants a quick update.

You can ask something like, "Show me my open tickets," and it’ll fetch a list. Simple enough. But the moment you try to have a real conversation, the cracks start to show. You might follow up with, "Okay, now just show me the ones from the ‘Website Redesign’ project." Instead of a filtered list, you could get a completely wrong answer or a frustrating, "I can’t access that information."

It feels like talking to someone with short-term memory loss. Here’s why this happens:

• It gives inaccurate or incomplete answers. The connector is terrible at remembering context. Every question you ask is often treated like a brand-new conversation, so it has no memory of what you were just discussing. This makes drilling down into specifics nearly impossible.

• Its knowledge is stuck in a silo. This is a huge one. The connector can only see what’s inside your Jira issues. But where does the real work happen? The project brief is probably in Google Docs, the crucial design feedback is buried in a Slack channel, and the technical specs are in a Confluence page. The AI can’t see any of that, so its answers are shallow and often miss the point entirely.

• It has some surprising technical blind spots. Even if you dig into Microsoft’s own documentation, you’ll find admissions of its shortcomings. The connector can’t index attachments within your Jira tickets, which is often where the most important files are. There can also be search delays, meaning that ticket you just updated might not show up in the results for a while.

Atlassian Intelligence: A native Jira Copilot (formerly Rovo)

Atlassian has been busy building its own AI, Atlassian Intelligence, right into its products. The goal is to make you faster inside the Atlassian world. It can do some genuinely handy things, like summarizing a novel-length comment thread on a ticket, drafting an issue description from a short prompt, or even writing a complex JQL search query for you. There’s also an Atlassian Rovo for GitHub Copilot extension to bring some of that context to developers in their code editor.

While these features can definitely speed up small, specific tasks in Jira, Atlassian Intelligence has its own set of limitations:

• It lives in a walled garden. Atlassian’s AI is at its most powerful when your company’s entire universe of knowledge lives within Atlassian products. But let’s be realistic, whose does? What happens when your most critical project information is in Google Docs, your team communicates in Slack, or your customer support history is logged in Zendesk? The AI is completely blind to all of it, leaving you with answers that are missing the bigger picture.

• It’s more of a "feature" than an "agent." It offers helpful shortcuts, but it doesn’t act like an independent assistant. It can’t be programmed to handle complex, multi-step tasks or configured to automatically resolve certain types of tickets from start to finish. It assists you, but it doesn’t work for you.

• The best features are behind a paywall. As we’ll get into next, accessing the really powerful AI capabilities means ponying up for a Premium or Enterprise Jira subscription, which can be a steep price jump for many teams.

The reality of setting up and paying for a Jira Copilot

The marketing brochures make AI integrations look like magic. Click a button, and you’re done! The reality is usually a maze of technical hurdles and hidden costs.

The surprisingly complex Jira Copilot setup

Getting the Microsoft Jira connector up and running is definitely not a simple, one-click install. You’ll need to roll up your sleeves and get pretty technical.

This video walks through the technical setup process for the Jira connector, highlighting the complexity involved.

If you follow Microsoft’s own documentation, here’s a taste of what you’re in for:

• First, you need to be a Microsoft 365 administrator just to begin the process.

• Then, you have to create a special service account in Jira and carefully grant it a specific list of permissions, like "Browse projects" and "Administer Jira".

• The recommended authentication method is OAuth 2.0. This means you have to go to the Atlassian Developer console to register an app, painstakingly configure over 20 different API permissions (or "scopes"), and then copy-paste client IDs and secret keys back and forth.

This isn’t something your average project manager can knock out on a Tuesday afternoon. It’s a project in itself that almost always requires pulling in someone from IT or a developer to get it right.

Understanding what a Jira Copilot really costs

A Jira Copilot isn’t a single line item on an invoice; it’s a stack of subscriptions that can add up fast. To get the Microsoft integration to work, every single person on your team who wants to use it needs a Copilot for Microsoft 365 license. That’s a separate, pricey subscription on top of the standard Microsoft 365 plan you’re already paying for.

Over on the Atlassian side, things are also tiered. While you get a few basic AI tricks on the free plan, the features you actually want are locked behind their paid plans. The really useful stuff, like Rovo Search and Agents, is only available on Standard plans and higher, and even then, your usage is capped by a system of "AI credits."

Here’s a rough look at Jira’s pricing and the AI features you get at each level:

When you do the math, you could easily end up paying for both a Microsoft Copilot license and a premium Jira plan for every single user, just to get a clunky integration that doesn’t even work that well.

A better Jira Copilot: The eesel AI approach

While the official connectors might work for very simple use cases, a dedicated AI platform designed for this specific problem offers a more powerful, flexible, and honestly, less frustrating solution. Here’s how a platform like eesel AI solves the core issues we’ve been talking about.

Go live with your Jira Copilot in minutes, not months

Remember that complicated, multi-step setup process for the official connectors? You can forget all about it. A truly self-serve platform like eesel AI lets you connect your Jira account and start seeing results in minutes. There are no mandatory sales calls to sit through or developer tickets to file. With simple, one-click integrations for Jira and other tools, you can have a working AI agent ready for testing almost immediately.

A Jira Copilot should unify all your knowledge, not just Jira tickets

The "walled garden" problem is the Achilles’ heel of the official integrations. The context you need to solve a Jira ticket is almost never just in Jira. It’s scattered everywhere: the project plans in Notion, the technical architecture diagrams in Google Docs, and the quick back-and-forth decisions in Slack.

eesel AI is built to break down those silos. It connects to over 100 different sources, so when you ask it a question, it trains on your entire knowledge ecosystem to get the full picture. It can even learn from how your team has resolved tickets in the past, allowing it to understand your unique business context and give answers that are far more accurate and genuinely useful.

eesel AI breaks down knowledge silos by connecting to over 100 sources, giving your Jira Copilot the full context.

Gain total Jira Copilot control with a customizable workflow engine

The standard copilots are pretty good at searching and summarizing, but that’s where their skills usually end. A real AI agent should be able to do things. eesel AI gives you a complete workflow engine that puts you in the driver’s seat. You can:

• Define custom actions. You can teach your AI to do more than just talk. Configure it to update ticket fields, add comments, apply the right labels to issues, or even call an API to trigger an action in a completely different system.

• Choose what to automate. You don’t have to flip a switch and automate everything at once. You can use selective automation to decide which kinds of Jira issues the AI should handle and which ones it should pass along to a human. Start small and expand as you get more confident.

• Test with confidence. This is a huge deal. eesel AI has a powerful simulation mode that lets you test your AI agent on thousands of your company’s historical Jira tickets before it ever talks to a real person. This gives you a clear, data-driven forecast of how it will perform and what its resolution rate will be, so you can deploy it without any of the usual risks.

The eesel AI simulation mode allows you to test your Jira Copilot on historical data before going live.

Move beyond a simple Jira Copilot connector

The idea of a Jira Copilot is a good one, but the official integrations from Microsoft and Atlassian are held back by some serious limitations in complexity, accuracy, and control. They behave more like simple search tools than true AI partners. They can find information (sometimes), but they can’t take meaningful action or understand the full story behind your work.

For teams who are serious about using AI to actually improve how they work in Jira, a dedicated, integrated platform is the way to go. It gives you the simplicity to get started fast, the power to connect all your scattered knowledge, and the control to build automated workflows that deliver real, measurable results.

Get started with a Jira Copilot that actually works

If you’re tired of clunky integrations and AI that feels more like a gimmick than a tool, it’s time to try a solution that was built for the job. eesel AI integrates seamlessly with Jira, learns from all your company knowledge, and gives you the power to automate with confidence.

Start Your Free Trial

Book a Demo